An Energy and Load Aware Multipath Routing Protocol in the Internet of Things

Internet of things (IoT) is a network of smart things. This indicates the ability of these physical things to transfer information with other physical things. The characteristics of these networks, such as topology dynamicity and energy constraint, challenges the routing problem in these networks. Previous routing methods could not achieve the required performance in this type of network. Therefore, developers of this network designed and developed specific methods in order to satisfy the requirements of these networks. One of the routing methods is utilization of multipath protocols which send data to its destination using routes with separate links. One of such protocols is RPL routing protocol. In this paper, this method is improved using composite metrics which chooses the best paths used for separate routes to send packets. We propose Energy and Load aware RPL (ELaM-IoT) protocol, which is an enhancement of RPL protocol. It uses a composite metric, calculated based on remaining energy, hop count, Link Expiration Time (LET), load and battery depletion index (BDI) for the route selection. In order to evaluate and report the results, the proposed ELaM-IoT method is compared to the ERGID and ADRM-IoT approaches with regard to average remaining energy, and network lifetime. The results demonstrate the superior performance of the proposed ELaM-IoT compared to the ERGID and ADRM-IoT approaches.

A Multiconstrained QoS-Compliant Routing Scheme for Highway-Based Vehicular Networks

With the deployment of multimedia services over VANETs, there is a need to develop new techniques to insure various levels of quality of services (QoS) for real time applications. However, in such environments, it is not an easy task to determine adequate routes to transmit data with specific application QoS requirements. In this paper, we propose CBQoS-Vanet, a new QoS-based routing protocol tailored towards vehicular networks in a highway scenario. This protocol is based on the use of two techniques: first a clustering technique which organizes and optimizes the exchange of routing information and, second, a bee colony inspired algorithm, which calculates the best routes from a source to a destination based on given QoS criteria. In our approach, clusters are formed around cluster heads that are themselves elected based on QoS considerations. The QoS criteria here are based on the two categories of metrics: QoS metrics and mobility metrics. The QoS metrics consists of the available bandwidth, the end-to-end delay, and the jitter. The mobility metrics consists of link expiration time and average velocity difference. We have studied the performance of CBQoS-Vanet through simulation and compared it to existing approaches. The results that we obtained show that our technique outperforms, in many aspects, the approaches that it was compared against.

Edge Centrality Metrics to Quantify the Stability of Links for Mobile Sensor Networks

In this chapter, we explore the use of neighborhood overlap (NOVER), bipartivity index (BPI) and algebraic connectivity (ALGC) as edge centrality metrics to quantify the stability of links for mobile sensor networks. In this pursuit, we employ the notion of the egocentric network of an edge (comprising of the end vertices of the edge and their neighbors as nodes, and the edges incident on the end vertices as links) on which the above three edge centrality metrics are computed. Unlike the existing approach of using the predicted link expiration time (LET), the computations of the above three edge centrality metrics do not require the location and mobility information of the nodes. For various scenarios of node density and mobility, we observe the stability of the network-wide data gathering trees (lifetime) determined using the proposed three edge centrality metrics to be significantly larger than the stability of the LET-based data gathering trees.

Neighborhood Overlap-based Stable Data Gathering Trees for Mobile Sensor Networks

The hypothesis in this research is that the end nodes of a short distance link (the distance between the end nodes is significantly smaller than the transmission range per node) in a mobile sensor network (MSN) are more likely to share a significant fraction of their neighbors and such links are more likely to be stable. The author proposes to use Neighborhood Overlap (NOVER), a graph-theoretic metric used in complex network analysis, to effectively quantify the extent of shared neighborhood between the end nodes of a link and thereby the stability of the link. The author's claim is that links with larger NOVER score are more likely to be stable and could be preferred for inclusion while determining stable data gathering trees for MSNs. Through extensive simulations, the author shows that the NOVER-based DG trees are significantly more stable and energy-efficient compared to the DG trees determined using the predicted link expiration time (LET). Unlike the LET approach (currently the best known strategy), the NOVER-based approach could be applied without knowledge about the location and mobility of the nodes.